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      Lower 30-day readmission rates with roflumilast treatment among patients hospitalized for chronic obstructive pulmonary disease

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          Abstract

          Background

          Few data exist related to the impact of roflumilast on health care utilization. This retrospective study estimated 30-day hospital readmission rates between patients who did and did not use roflumilast among those with COPD hospitalizations.

          Methods

          Data were from MarketScan, a large US commercial health insurance claims database. Patients aged ≥40 years with at least one hospitalization for COPD between 2010 and 2011 were included. The roflumilast group included patients who used roflumilast within 14 days after the first hospitalization (index), while the comparison group (non-roflumilast) included patients who did not use roflumilast during the study period. Continuous enrollment for at least 6 months before and 30 days after the index date was required. The 30-day hospitalization rate was calculated after the index hospitalization. Conditional logistic regression with propensity score 1:3 matching was employed to assess the difference in 30-day hospital readmission rates between the roflumilast and non-roflumilast groups, adjusting for baseline characteristics, comorbidity, health care utilization, and COPD medication use within 14 days after the index date.

          Results

          A total of 15,755 COPD patients met the selection criteria, ie, 366 (2.3%) in the roflumilast group and 15,389 (97.7%) in the non-roflumilast group. The mean (± standard deviation) age was 71±12.5 years and 52% were female. After propensity score matching, all-cause 30-day hospitalization rates were 6.9% and 11.1% in the roflumilast and non-roflumilast groups, respectively. COPD-related 30-day hospitalization rates were 6.3% and 9.2% in the roflumilast and non-roflumilast groups, respectively. Conditional logistic regression identified a significantly lower likelihood of all-cause 30-day readmission (odds ratio 0.59, 95% confidence interval 0.37–0.93, P=0.023) for roflumilast patients relative to non-roflumilast patients.

          Conclusion

          This study showed, in a real-world setting, that use of roflumilast was associated with a lower rate of hospital readmission within 30 days among patients hospitalized for COPD.

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          Most cited references 16

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          The costs of exacerbations in chronic obstructive pulmonary disease (COPD).

          Exacerbations are the key drivers in the costs of chronic obstructive pulmonary disease (COPD). The objective was to examine the costs of COPD exacerbations in relation to differing degrees of severity of exacerbations and of COPD. We identified 202 subjects with COPD, defined according to the BTS and ERS criteria. Exacerbations were divided into mild (self-managed), mild/moderate (telephone contact with a health-care centre and/or the use of antibiotics/systemic corticosteroids), moderate (health-care centre visits) and severe (emergency care visit or hospital admission). Exacerbations were identified by sending the subjects a letter inquiring whether they had any additional respiratory problems or influenza the previous winter. At least one exacerbation was reported by 61 subjects, who were then interviewed about resource use for these events. The average health-care costs per exacerbation were SEK 120 (95% C=39-246), SEK 354 (252-475), SEK 2111 (1673-2612) and SEK 21852 (14436-29825) for mild, mild/moderate, moderate and severe exacerbations, respectively. Subjects with impaired lung function experienced more severe exacerbations, which was also reflected in the cost of exacerbations per severity of the disease during the 4 1/2 month study period (ranging from SEK 224 for mild to SEK 13708 for severe cases, median SEK 940). Exacerbations account for 35-45% of the total per capita health-care costs for COPD. In conclusion, costs varied considerably with the severity of the exacerbation as well as with the severity of COPD. The prevention of moderate-to-severe exacerbations could be very cost-effective and improve the quality of life.
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            Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease

             K. Rabe,  SS Hurd,  A Anzueto (2016)
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              • Article: not found

              Predicting pharmacy costs and other medical costs using diagnoses and drug claims.

              Predicting health care costs for individuals and populations is essential for managing care. However, the comparative power of diagnostic and drug data for predicting future costs has not been closely examined. We sought to compare the predictive performance of claims-based models using diagnoses, drugs claims, and combined data to predict health care costs. More than 1 million commercially insured, nonelderly individuals in a national (MEDSTAT MarketScan) research database comprised our sample. We used 1997 and 1998 drug and diagnostic profiles to predict costs in 1998 and 1999, respectively. To assess model performance, we compared R2 values and predictive ratios (predicted costs/actual costs) for important subgroups. Models using both drug and diagnostic data best predicted subsequent-year total health care costs (highest R2 = 0.168 versus 0.116 and 0.146 for models based on drug or diagnostic data alone, respectively), with highly accurate predictive ratios (0.95-1.05) for subgroups of patients with major medical conditions. Models predicting pharmacy costs had substantially higher R2 values than models predicting other medical costs (highest R2 0.493 versus 0.124). Drug-based models predicted future pharmacy costs better than diagnosis-based models (highest R2 = 0.482 versus 0.243), whereas diagnosis-based models predicted total costs (highest R2 = 0.146 versus 0.116) and nonpharmacy costs (highest R2 = 0.116 versus 0.071) more effectively than drug-based models. Newer models had markedly higher R values than older ones, largely because of richer data rather than model refinements. Combined drug and diagnostic data predicts total health care costs better than either type of data alone. Pharmacy spending is particularly predictable from drug data, whereas diagnoses are more useful than drugs for predicting other medical costs and total costs. Using even slightly more recent data can substantially boost model performance measures; thus, model comparisons should be conducted on the same dataset.
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                Author and article information

                Journal
                Int J Chron Obstruct Pulmon Dis
                Int J Chron Obstruct Pulmon Dis
                International Journal of COPD
                International Journal of Chronic Obstructive Pulmonary Disease
                Dove Medical Press
                1176-9106
                1178-2005
                2015
                12 May 2015
                : 10
                : 909-915
                Affiliations
                [1 ]Georgetown University Medical Center, Washington, DC, USA
                [2 ]Health Economics and Outcomes Research, Forest Laboratories, LLC, an affiliate of Actavis, Inc., Jersey City, NJ, USA
                [3 ]Department of Medicine, University of California, Irvine, CA, USA
                Author notes
                Correspondence: Alex Z Fu, Georgetown University Medical Center, 3300 Whitehaven Street, NW, Suite 4100, Washington, DC 20007, USA, Email zf54@ 123456georgetown.edu
                Article
                copd-10-909
                10.2147/COPD.S83082
                4435078
                25999706
                © 2015 Fu et al. This work is published by Dove Medical Press Limited, and licensed under Creative Commons Attribution – Non Commercial (unported, v3.0) License

                The full terms of the License are available at http://creativecommons.org/licenses/by-nc/3.0/. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.

                Categories
                Original Research

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